Analysis of the levels of lysine-specific demethylase 1 (LSD1) mRNA in human ovarian tumors and the effects of chemical LSD1 inhibitors in ovarian cancer cell lines

BACKGROUND: Lysine-specific demethylase 1 (LSD1, also known as KDM1A and AOF2) is a chromatin-modifying activity that catalyzes the removal of methyl groups from lysine residues in histone and non-histone proteins, regulating gene transcription. LSD1 is overexpressed in several cancer types, and chemical inhibition of the LSD1 activity has been proposed as a candidate cancer therapy. Here, we examine the levels of LSD1 mRNA in human ovarian tumors and the cytotoxicity of several chemical LSD1 inhibitors in a panel of ovarian cancer cell lines. METHODS: We measured LSD1 mRNA levels in a cohort of n = 177 normal and heterogeneous tumor specimens by quantitative real time-PCR (qRT-PCR). Tumors were classified by FIGO stage, FIGO grade, and histological subtypes. We tested the robustness of our analyses in an independent cohort of n = 573 serous tumor specimens (source: TCGA, based on microarray). Statistical analyses were based on Kruskal-Wallis/Dunn’s and Mann Whitney tests. Changes in LSD1 mRNA levels were also correlated with transcriptomic alterations at genome-wide scale. Effects on cell viability (MTS/PMS assay) of six LSD1 inhibitors (pargyline, TCP, RN-1, S2101, CAS 927019-63-4, and CBB1007) were also evaluated in a panel of ovarian cancer cell lines (SKOV3, OVCAR3, A2780 and cisplatin-resistant A2780cis). RESULTS: We found moderate but consistent LSD1 mRNA overexpression in stage IIIC and high-grade ovarian tumors. LSD1 mRNA overexpression correlated with a transcriptomic signature of up-regulated genes involved in cell cycle and down-regulated genes involved in the immune/inflammatory response, a signature previously observed in aggressive tumors. In fact, some ovarian tumors showing high levels of LSD1 mRNA are associated with poor patient survival. Chemical LSD1 inhibition induced cytotoxicity in ovarian cancer lines, which roughly correlated with their reported LSD1 inhibitory potential (RN-1,S2101 >> pargyline,TCP). CONCLUSIONS: Our findings may suggest a role of LSD1 in the biology of some ovarian tumors. It is of special interest to find a correlation of LSD1 mRNA overexpression with a transcriptomic signature relevant to cancer. Our findings, therefore, prompt further investigation of the role of LSD1 in ovarian cancer, as well as the study of its enzymatic inhibition in animal models for potential therapeutic purposes in the context of this disease

Decoding a signature-based model of transcription cofactor recruitment dictated by cardinal cis-regulatory elements in proximal promoter regions.

Genome-wide maps of DNase I hypersensitive sites (DHSs) reveal that most human promoters contain perpetually active cis-regulatory elements between -150 bp and +50 bp (-150/+50 bp) relative to the transcription start site (TSS). Transcription factors (TFs) recruit cofactors (chromatin remodelers, histone/protein-modifying enzymes, and scaffold proteins) to these elements in order to organize the local chromatin structure and coordinate the balance of post-translational modifications nearby, contributing to the overall regulation of transcription. However, the rules of TF-mediated cofactor recruitment to the -150/+50 bp promoter regions remain poorly understood. Here, we provide evidence for a general model in which a series of cis-regulatory elements (here termed 'cardinal' motifs) prefer acting individually, rather than in fixed combinations, within the -150/+50 bp regions to recruit TFs that dictate cofactor signatures distinctive of specific promoter subsets. Subsequently, human promoters can be subclassified based on the presence of cardinal elements and their associated cofactor signatures. In this study, furthermore, we have focused on promoters containing the nuclear respiratory factor 1 (NRF1) motif as the cardinal cis-regulatory element and have identified the pervasive association of NRF1 with the cofactor lysine-specific demethylase 1 (LSD1/KDM1A). This signature might be distinctive of promoters regulating nuclear-encoded mitochondrial and other particular genes in at least some cells. Together, we propose that decoding a signature-based, expanded model of control at proximal promoter regions should lead to a better understanding of coordinated regulation of gene transcription

Система охолодження наддувного повітря суднового двигуна внутрішнього згоряння термопресором з упорскуванням перегрітої води

Коновалов, Д. В. Система охолодження наддувного повітря суднового двигуна внутрішнього згоряння термопресором з упорскуванням перегрітої води = The charge air cooling system of the ship's internal combustion engine by the thermopressor with overheating water injection / Д. В. Коновалов, Г. О. Кобалава, С. І. Стародубець // Авиационно-космическая техника и технология : науч.-техн. журн. – Харьков : ХАИ, 2017.– № 3 (138). – С. 104–111.Проаналізовано схемне рішення із застосуванням термопресора в складі багатоконтурної системи охолодження середньообертового двигуна суднової енергетичної установки. Розглянуто спосіб підвищення ефективності процесу розпилення перегрітої відносно температури насиченняводи в термопресорі. Як показали дослідження, застосування перегрітої води для упорскування в термопресор системи охолодження наддувного повітря суднових двигунів дає можливість збільшити відносне підвищення тиску повітря на виході з термопресора на 5...8 %, з відповідним зменшенням потужності турбокомпресора двигуна.The scheme solution by using thermopressor as the part of three-circuit cooling system of the medium-speed marine engine is analyzed. The way to improve of the efficiency of the water spray process in the thermopressor is considered. Using of overheated water injection in the thermopressor of the charge air cooling system makes it possible to increase the relative increase air pressure at the outlet thermopressor to 5...8 %, with a corresponding reduc-tion in the power of the engine turbocharger

Decoding a Signature-Based Model of Transcription Cofactor Recruitment Dictated by Cardinal Cis-Regulatory Elements in Proximal Promoter Regions

<div><p>Genome-wide maps of DNase I hypersensitive sites (DHSs) reveal that most human promoters contain perpetually active cis-regulatory elements between −150 bp and +50 bp (−150/+50 bp) relative to the transcription start site (TSS). Transcription factors (TFs) recruit cofactors (chromatin remodelers, histone/protein-modifying enzymes, and scaffold proteins) to these elements in order to organize the local chromatin structure and coordinate the balance of post-translational modifications nearby, contributing to the overall regulation of transcription. However, the rules of TF-mediated cofactor recruitment to the −150/+50 bp promoter regions remain poorly understood. Here, we provide evidence for a general model in which a series of cis-regulatory elements (here termed ‘cardinal’ motifs) prefer acting individually, rather than in fixed combinations, within the −150/+50 bp regions to recruit TFs that dictate cofactor signatures distinctive of specific promoter subsets. Subsequently, human promoters can be subclassified based on the presence of cardinal elements and their associated cofactor signatures. In this study, furthermore, we have focused on promoters containing the nuclear respiratory factor 1 (NRF1) motif as the cardinal cis-regulatory element and have identified the pervasive association of NRF1 with the cofactor lysine-specific demethylase 1 (LSD1/KDM1A). This signature might be distinctive of promoters regulating nuclear-encoded mitochondrial and other particular genes in at least some cells. Together, we propose that decoding a signature-based, expanded model of control at proximal promoter regions should lead to a better understanding of coordinated regulation of gene transcription.</p></div

Signature of cofactors associated with the enrichment of a specific cardinal motif.

<p><i>(</i><b><i>A</i></b><i>)</i> Heatmap analysis of relative enrichment of cardinal motifs in proximal promoter regions occupied by different proteins, based on >60 ChIP-seq datasets: n = 8 TF ChIP-seq datasets (labeled in red) and n = 59 cofactors/others ChIP-seq datasets (labeled in black). Sources of ChIP-seq experiments: ENCODE (accession number and/or laboratory are included in parenthesis); and NRF1, NFYB, and LSD1 datasets were generated in this study. The vector of motif enrichment for each experiment was normalized and centered on the mean value to reveal the preferences of each experiment for cardinal motifs. The analysis shows negative log of the hypergeometric <i>p</i>-value. <i>(</i><b><i>B</i></b><i>)</i> List of cofactors associated with each cardinal motif, based on (<i>A</i>). <i>(</i><b><i>C</i></b><i>)</i> Model of signatures of cofactors associated with the presence of a specific cardinal motif (see text for details).</p

A series of cis-regulatory elements (here termed ‘cardinal’ motifs) are highly enriched at −150/+50 bp relative to TSS (+1) and may define different subsets of human promoters.

<p>(<b><i>A</i></b>) Most human promoters contain ‘open’ chromatin regions at −150/+50 bp relative to +1, or TSS. These regions are surrounded by heavily modified nucleosomes containing H3K4me2/3 (depicted in red in the vignette). We have identified the most enriched cis-regulatory elements in these particular regions by <i>de novo</i> motif discovery analysis of n = 21,000 human promoters. The panel shows rank of element enrichment, fraction of promoters containing these elements, consensus sequence, and cognate TF when known (e.g. NRF1 or NFY) or when proposed (e.g. Clus1). We refer to these elements as ‘cardinal’ motifs, and to the TFs that recognize them as ‘cardinal’ TFs. (<b><i>B</i></b>) Analysis of motif co-occurrences among cardinal motifs. <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003906#s2" target="_blank">Results</a> are shown as a matrix of co-occurrences based on the analysis of n = 21,000 human promoters (−150/+50 bp). Co-occurrence log₂<i>p</i>-values are shown as a gradient of blue-to-red for positive-to-negative co-occurrences, and as white in the absence of significant co-occurrence. (<b><i>C</i></b>) Positional binding analysis of cardinal TFs NRF1 (red) and NFYB (blue) with respect to −150/+50 bp genomic regions in MCF7 cells, based on ChIP-seq data. The x-axis refers to genomic distances with respect to −150/+50 bp (center of the panel). Genomic windows span: 200 bp (between −150/+50 bp and ±2 kb), 1 kb (between ±2 kb and ±10 kb), and the rest of distances together (beyond ±10 kb). The y-axis refers to percentage of the total of NRF1 and NFYB peaks in each genomic range. The total number of peaks (n) and the specific number of peaks within −150/+50 bp regions (n) are also indicated in the panel. (<b><i>D</i></b>) Meta-analysis of sequencing read density based on DNaseI-seq (top) and H3K4me2 MNase-seq (bottom) around NRF1 (red) and NFYB (blue) ChIP-seq peaks (both at the center of the panel). (<b><i>E</i></b>) Venn diagram depicting the overlap of RNA PolII (grey circle), NRF1 (red circle), and NFYB (blue circle) ChIP-seq peaks in MCF7 cells. We considered as ‘overlap’ the coincidence of NRF1 and NFYB peaks in the same −150/+50 bp region. Also, we considered as ‘overlap’ the coincidence of RNA PolII peaks within ±1 kb of a TSS containing NRF1 or NFYB peaks at −150/+50 bp. <i>(</i><b><i>F</i></b><i>)</i> Functional (gene ontology, or GO) analysis of genes with NRF1 (top) or NFYB (bottom) ChIP-seq peaks in their −150/+50 bp regions. <i>P</i>-values (log scale) are shown in the <i>x</i>-axis. GO terms are indicated in the y-axis.</p

Diversity of functional outcomes associated with NRF1/LSD1 recruitment at −150/+50 bp regions.

<p><i>(</i><b><i>A</i></b><i>)</i> Left: Western blot analysis of NRF1 and LSD1 in whole cell extracts obtained from MCF7 cells in which NRF1 or LSD1 (indicated on top) were depleted by siRNA. Actin is shown as loading control. Scrambled (CTL) siRNA is included as control of transfection. Panels: RT-qPCR analysis of genes that have been identified in this study as having promoters co-occupied by NRF1 and LSD1 (NRF1⁺ and LSD1⁺ targets). Gene names are indicated on top of each panel. Treatments are indicated at the bottom. Scrambled (CTL) siRNA was used as control. The y-axis refers to normalized expression to levels of <i>ACTB</i> mRNA. <i>(</i><b><i>B</i></b><i>)</i> Top: Western blot analysis as shown in <b><i>A</i></b> (left panel) but in U2OS cells. Bottom: Venn diagram depicting the overlap of genes affected by <i>NRF1</i> (light red circle) and <i>LSD1</i> (orange circle) siRNA treatments with respect to control (CTL) siRNA in U2OS cells, based on microarray. The number of total and category-wise genes affected by the treatments are indicated, as well as the statistical significance of the overlap. <i>(</i><b><i>C</i></b><i>)</i> Matrix of motif enrichment of cardinal motifs in −150/+50 bp regions of genes identified by microarray as affected by <i>NRF1</i> (left) or <i>LSD1</i> (right) knockdown in U2OS cells. Enrichment levels were determined with respect to background frequencies of the same motifs in −150/+50 bp regions. Motif enrichments higher than background are shown as a gradient of blue, while motif enrichments lower than background are shown as a gradient of red. No motif enrichment is shown as white. The number of promoters analyzed is also indicated. <i>(</i><b><i>D</i></b><i>)</i> Venn diagram depicting the overlap of microarray-identified genes classified based on their type of response to <i>NRF1</i> or <i>LSD1</i> siRNA treatments. The numbers of genes in the overlaps are indicated, as well as the numbers of genes that did not overlap and the total numbers. <i>(</i><b><i>E</i></b><i>)</i> Combined analysis of microarray and ChIP-based data. We combined microarray results identifying <i>NRF1</i> and/or <i>LSD1</i> siRNA-mediated effects and ChIP-DSL data identifying <i>NRF1</i> and/or <i>LSD1</i> occupied promoters. Gene classes based on (<i>D</i>). The y-axis refers to the relative enrichment over background in the number of genes that were affected by both <i>NRF1</i> and <i>LSD1</i> siRNA treatments and that had promoters occupied by LSD1 (orange) and/or NRF1 (red; see text for more details). A ratio of ‘fold over background’ higher or lower than 1 (>1 or <1, respectively) distinguishes when a gene class contains a higher or lower frequency of either LSD1- or NRF1-occupied promoters over the frequency observed in genes not affected by <i>LSD1</i> or <i>NRF1</i> siRNA treatments (which we defined as ‘background’). <i>(</i><b><i>F</i></b><i>)</i> As in <b><i>E</i></b>, but for genes that were affected only by either <i>NRF1</i> or <i>LSD1</i> siRNA treatments.</p

Cardinal motifs dictate patterns of transcriptional regulatory activities.

<p><i>(</i><b><i>A</i></b><i>)</i> Schematic overview of the siRNA-based screen to identify lysine demethylase (KDM) activities that may act selectively via NRF1 or NFYB motifs. KDMs belong to two gene families: the family of amine oxidase flavin (AOF)-containing domain proteins, and the family of Jumonji C (JmjC)-containing proteins. HEK293T cells were transfected with a vector expressing the luciferase gene under control of three multimerized copies of NRF1 (3×NRF1, left side of the scheme) or three multimerized copies of NFY (3×NFY, right side of the scheme). Luciferase levels were tested after independent treatment with n = 27 different KDM siRNAs, plus controls. <i>(</i><b><i>B</i></b><i>)</i> Summary of siRNA-mediated effects that showed selectivity for 3×NRF1 or 3×NFY motifs in our screen. A total of n = 14 out of n = 27 siRNA treatments induced selective effects: n = 6 were selective of the presence of 3×NRF1 (top), and n = 8 were selective of the presence of 3×NFY (bottom). Of these n = 14 siRNA treatments, furthermore, n = 8 induced down-regulation of the reported gene (left), and n = 6 induced its up-regulation (right). Selectivity for 3×NRF1 or 3×NFY motifs was established by the direct comparison of siRNA-mediated effects induced by the same siRNA treatment on 3×NRF1- or 3×NFY-luciferase ((<i>p</i><0.05; last row in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003906#pgen.1003906.s003" target="_blank">Figure S3A</a></b>). In n = 11 out of the n = 14 treatments (red circles if selective of 3×NRF1, or blue circles if selective of 3×NFY), the difference between the specific KDM and control (scrambled) siRNA-mediated effect was also statistically significant (<i>p</i><0.05; first and second rows in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003906#pgen.1003906.s003" target="_blank">Figure S3A</a></b>). In the other n = 3 out of the n = 14 selective siRNA treatments (red-and-blue circles), the difference with respect to control siRNA was statistically significant for both 3×NRF1- and 3×NFY-regulated units, although statistically significant also when compared between them (<i>p</i><0.05; last row in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003906#pgen.1003906.s003" target="_blank">Figure S3A</a></b>). <i>(</i><b><i>C</i></b><i>)</i> Positional binding analysis of LSD1 in MCF7 cells (as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003906#pgen-1003906-g001" target="_blank"><b>Figure 1C</b></a>), and genomic localization of LSD1 ChIP-seq peaks with respect to the genome annotation (pie chart). The numbers included in the pie chart refer to the fraction of LSD1 peaks associated with each annotated region. <i>(</i><b><i>D</i></b><i>)</i> Venn diagram depicting the overlap of LSD1 (orange), NRF1 (red), and NFYB (blue) ChIP-seq peaks at −150/+50 bp regions in MCF7 cells. We considered as ‘overlap’ the coincidence of NRF1, NFYB, and/or LSD1 peaks in the same −150/+50 bp region.</p

Cardinal motif NRF1 dictates the recruitment of KDM LSD1 via TF NRF1.

<p><i>(</i><b><i>A</i></b><i>)</i> Representative examples of ChIP-seq tracks showing precise co-alignment of NRF1 and LSD1. These particular loci (<i>ZWINT</i> and <i>LINS-ASB7</i>) were selected as representative despite being rare examples in which NRF1 binds nearby NFYB, but they should help to emphasize the good co-alignment between LSD1 and NRF1 using NFYB as reference. The track of ChIP-seq data for H3K4me3 was also included as reference. Annotation of Ref-seq genes is included. <i>(</i><b><i>B</i></b><i>)</i> Meta-analysis of sequencing read density of LSD1 ChIP-seq (orange) and NRF1 ChIP-seq (red) signals around NRF1 peaks (center of the panel). <i>(</i><b><i>C</i></b><i>)</i> Left: Scheme of two constructs engineered to contain 3× wild-type NRF1 sequences (3xwtNRF1, as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003906#pgen-1003906-g002" target="_blank"><b>Figure 2A</b></a>) or 3× mutated NRF1 sequences (3xmutNRF1) upstream the luciferase reporter gene. Panels: Luciferase assay with 3xwtNRF1- or 3xmutNRF1-transected U2OS cells (left panel) and ChIP analyses of NRF1 and LSD1 at 3xwtNRF1 and 3xmutNRF1 sites (middle and right panels, respectively). For ChIP analyses, two regions were amplified (labeled in the scheme, left): one region covering 3xwtNRF1 or 3xmutNRF1 sites (depending on the construct), amplified with primers named as ‘site’; and the other region covering a distal, control area (the same in both constructs), amplified with primers named as ‘ctl’. <i>(</i><b><i>D</i></b><i>)</i> Co-immunoprecipitation (IP) assay with the set of antibodies indicated on top of the panel, and detection with the set of antibodies indicated in the left of the panel. <i>(</i><b><i>E</i></b><i>)</i> Size exclusion chromatography (Superose 6) of nuclear extracts obtained from MCF7 cells. Analysis of elution fractions by Western blot using anti-LSD1 (top) and anti-NRF1 (bottom) antibodies. On top of the Western blot, elution of known molecular size markers is indicated (arrows). Voided volume was determined with Blue Dextran 2000 (>2MDa).</p